feat: allow use_graph for metrics

docs/conf.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import os
+import shutil
 import sys
 from datetime import datetime
 from functools import partial
@@ -13,6 +14,7 @@
 import matplotlib  # noqa
 from docutils import nodes
 from packaging.version import Version
+from sphinxcontrib.katex import NODEJS_BINARY
 
 # Don’t use tkinter agg when importing scanpy → … → matplotlib
 matplotlib.use("agg")
@@ -52,7 +54,6 @@
 bibtex_bibfiles = ["references.bib"]
 bibtex_reference_style = "author_year"
 
-
 # default settings
 templates_path = ["_templates"]
 master_doc = "index"
@@ -73,10 +74,10 @@
     "sphinx.ext.intersphinx",
     "sphinx.ext.doctest",
     "sphinx.ext.coverage",
-    "sphinx.ext.mathjax",
     "sphinx.ext.napoleon",
     "sphinx.ext.autosummary",
     "sphinxcontrib.bibtex",
+    "sphinxcontrib.katex",
     "matplotlib.sphinxext.plot_directive",
     "sphinx_autodoc_typehints",  # needs to be after napoleon
     "git_ref",  # needs to be before scanpydoc.rtd_github_links
@@ -129,6 +130,8 @@
 pygments_style = "default"
 pygments_dark_style = "native"
 
+katex_prerender = shutil.which(NODEJS_BINARY) is not None
+
 intersphinx_mapping = dict(
     anndata=("https://anndata.readthedocs.io/en/stable/", None),
     bbknn=("https://bbknn.readthedocs.io/en/latest/", None),

docs/release-notes/3898.feat.md

@@ -0,0 +1 @@
+Allow specifying graphs in {mod}`scanpy.metrics` functions {smaller}`P Angerer`

pyproject.toml

@@ -123,6 +123,7 @@ doc = [
     "nbsphinx>=0.9",
     "ipython>=7.20",                    # for nbsphinx code highlighting
     "sphinxcontrib-bibtex",
+    "sphinxcontrib-katex",
     # TODO: remove necessity for being able to import doc-linked classes
     "scanpy[paga,dask-ml,leiden]",
     "sam-algorithm",

src/scanpy/metrics/_common.py

@@ -9,6 +9,7 @@
 import pandas as pd
 
 from .._compat import CSRBase, DaskArray, SpBase, fullname, warn
+from .._utils import NeighborsView
 
 if TYPE_CHECKING:
     from typing import NoReturn
@@ -65,17 +66,22 @@ def __call__(self) -> np.ndarray:
                 raise NotImplementedError(msg)
 
 
-def _get_graph(adata: AnnData, *, use_graph: str | None = None) -> CSRBase:
+def _get_graph(
+    adata: AnnData,
+    *,
+    use_graph: str | None = None,
+    neighbors_key: str | None = None,
+) -> CSRBase:
     if use_graph is not None:
-        raise NotImplementedError()
-    # Fix for anndata<0.7
-    if hasattr(adata, "obsp") and "connectivities" in adata.obsp:
-        return adata.obsp["connectivities"]
-    elif "neighbors" in adata.uns:
-        return adata.uns["neighbors"]["connectivities"]
-    else:
+        if neighbors_key is not None:
+            msg = "Cannot specify both `use_graph` and `neighbors_key`."
+            raise TypeError(msg)
+        return adata.obsp[use_graph]
+    nv = NeighborsView(adata, neighbors_key)
+    if "connectivities" not in nv:
         msg = "Must run neighbors first."
         raise ValueError(msg)
+    return nv["connectivities"]
 
 
 @overload

src/scanpy/metrics/_gearys_c.py

@@ -9,7 +9,9 @@
 import numpy as np
 
 from .._compat import CSRBase, njit
+from .._utils import _doc_params
 from ..get import _get_obs_rep
+from ..neighbors._doc import doc_neighbors_key
 from ._common import _get_graph, _SparseMetric
 
 if TYPE_CHECKING:
@@ -20,12 +22,14 @@
 
 
 @singledispatch
+@_doc_params(neighbors_key=doc_neighbors_key)
 def gearys_c(
     adata_or_graph: AnnData | CSRBase,
     /,
     vals: _Vals | None = None,
     *,
     use_graph: str | None = None,
+    neighbors_key: str | None = None,
     layer: str | None = None,
     obsm: str | None = None,
     obsp: str | None = None,
@@ -42,11 +46,11 @@ def gearys_c(
     .. math::
 
         C =
-        \frac{
-            (N - 1)\sum_{i,j} w_{i,j} (x_i - x_j)^2
-        }{
-            2W \sum_i (x_i - \bar{x})^2
-        }
+        \frac{{
+            (N - 1)\sum_{{i,j}} w_{{i,j}} (x_i - x_j)^2
+        }}{{
+            2W \sum_i (x_i - \bar{{x}})^2
+        }}
 
     Params
     ------
@@ -60,8 +64,10 @@ def gearys_c(
         object by using key word arguments: `layer`, `obsm`, `obsp`, or
         `use_raw`.
     use_graph
-        Key to use for graph in anndata object. If not provided, default
-        neighbors connectivities will be used instead.
+        Key to use for graph in anndata object.
+        If not provided, default neighbors connectivities will be used instead.
+        (See ``neighbors_key`` below.)
+    {neighbors_key}
     layer
         Key for `adata.layers` to choose `vals`.
     obsm
@@ -96,7 +102,7 @@ def gearys_c(
 
     """
     adata = cast("AnnData", adata_or_graph)
-    g = _get_graph(adata, use_graph=use_graph)
+    g = _get_graph(adata, use_graph=use_graph, neighbors_key=neighbors_key)
     if vals is None:
         vals = _get_obs_rep(adata, use_raw=use_raw, layer=layer, obsm=obsm, obsp=obsp).T
     return gearys_c(g, vals)

src/scanpy/metrics/_morans_i.py

@@ -9,7 +9,9 @@
 import numpy as np
 
 from .._compat import CSRBase, njit
+from .._utils import _doc_params
 from ..get import _get_obs_rep
+from ..neighbors._doc import doc_neighbors_key
 from ._common import _get_graph, _SparseMetric
 
 if TYPE_CHECKING:
@@ -20,12 +22,14 @@
 
 
 @singledispatch
+@_doc_params(neighbors_key=doc_neighbors_key)
 def morans_i(
     adata_or_graph: AnnData | CSRBase,
     /,
     vals: _Vals | None = None,
     *,
     use_graph: str | None = None,
+    neighbors_key: str | None = None,
     layer: str | None = None,
     obsm: str | None = None,
     obsp: str | None = None,
@@ -40,11 +44,11 @@ def morans_i(
     .. math::
 
         I =
-            \frac{
-                N \sum_{i, j} w_{i, j} z_{i} z_{j}
-            }{
-                S_{0} \sum_{i} z_{i}^{2}
-            }
+            \frac{{
+                N \sum_{{i,j}} w_{{i,j}} z_{{i}} z_{{j}}
+            }}{{
+                S_{{0}} \sum_{{i}} z_{{i}}^{{2}}
+            }}
 
     Params
     ------
@@ -58,8 +62,10 @@ def morans_i(
         object by using key word arguments: `layer`, `obsm`, `obsp`, or
         `use_raw`.
     use_graph
-        Key to use for graph in anndata object. If not provided, default
-        neighbors connectivities will be used instead.
+        Key to use for graph in anndata object.
+        If not provided, default neighbors connectivities will be used instead.
+        (See ``neighbors_key`` below.)
+    {neighbors_key}
     layer
         Key for `adata.layers` to choose `vals`.
     obsm
@@ -94,7 +100,7 @@ def morans_i(
 
     """
     adata = cast("AnnData", adata_or_graph)
-    g = _get_graph(adata, use_graph=use_graph)
+    g = _get_graph(adata, use_graph=use_graph, neighbors_key=neighbors_key)
     if vals is None:
         vals = _get_obs_rep(adata, use_raw=use_raw, layer=layer, obsm=obsm, obsp=obsp).T
     return morans_i(g, vals)

src/scanpy/neighbors/_doc.py

@@ -1,5 +1,14 @@
 from __future__ import annotations
 
+doc_neighbors_key = """\
+neighbors_key
+    Where to look for neighbors connectivities.
+    If not specified, this retrieves ``.obsp['connectivities']`` for connectivities
+    (default storage place for :func:`~scanpy.pp.neighbors`).
+    If specified, this retrieves
+    ``.obsp[.uns[neighbors_key]['connectivities_key']]`` for connectivities.
+"""
+
 doc_use_rep = """\
 use_rep
     Use the indicated representation. `'X'` or any key for `.obsm` is valid.

src/scanpy/plotting/_docs.py

@@ -2,6 +2,8 @@
 
 from __future__ import annotations
 
+from ..neighbors._doc import doc_neighbors_key
+
 doc_adata_color_etc = """\
 adata
     Annotated data matrix.
@@ -22,19 +24,14 @@
     takes precedence over `use_raw`.\
 """
 
-doc_edges_arrows = """\
+doc_edges_arrows = f"""\
 edges
     Show edges.
 edges_width
     Width of edges.
 edges_color
     Color of edges. See :func:`~networkx.drawing.nx_pylab.draw_networkx_edges`.
-neighbors_key
-    Where to look for neighbors connectivities.
-    If not specified, this looks .obsp['connectivities'] for connectivities
-    (default storage place for pp.neighbors).
-    If specified, this looks
-    .obsp[.uns[neighbors_key]['connectivities_key']] for connectivities.
+{doc_neighbors_key}
 arrows
     Show arrows (deprecated in favour of `scvelo.pl.velocity_embedding`).
 arrows_kwds

src/scanpy/preprocessing/_highly_variable_genes.py

@@ -363,10 +363,6 @@ def _highly_variable_genes_single_batch(
     if n_removed:
         x = x[:, filt].copy()
 
-    if hasattr(x, "_view_args"):  # AnnData array view
-        # For compatibility with anndata<0.9
-        x = x.copy()  # Doesn't actually copy memory, just removes View class wrapper
-
     if flavor == "seurat":
         x = x.copy()
         if (base := adata.uns.get("log1p", {}).get("base")) is not None:

tests/test_metrics.py

@@ -9,6 +9,7 @@
 import pandas as pd
 import pytest
 import threadpoolctl
+from anndata import AnnData
 from scipy import sparse
 
 import scanpy as sc
@@ -79,10 +80,12 @@ def test_consistency(metric) -> None:
         pytest.param(sc.metrics.morans_i, 50, 1.0, id="morans_i"),
     ],
 )
-def test_correctness(metric, size, expected):
+def test_correctness(metric, size, expected) -> None:
+    rng = np.random.default_rng()
+
     # Test case with perfectly seperated groups
     connected = np.zeros(100)
-    connected[np.random.choice(100, size=size, replace=False)] = 1
+    connected[rng.choice(100, size=size, replace=False)] = 1
     graph = np.zeros((100, 100))
     graph[np.ix_(connected.astype(bool), connected.astype(bool))] = 1
     graph[np.ix_(~connected.astype(bool), ~connected.astype(bool))] = 1
@@ -93,9 +96,6 @@ def test_correctness(metric, size, expected):
         metric(graph, connected),
         metric(graph, sparse.csr_matrix(connected)),  # noqa: TID251
     )
-    # Checking that obsp works
-    adata = sc.AnnData(sparse.csr_matrix((100, 100)), obsp={"connectivities": graph})  # noqa: TID251
-    np.testing.assert_equal(metric(adata, vals=connected), expected)
 
 
 @pytest.mark.usefixtures("_threading")
@@ -104,18 +104,20 @@ def test_correctness(metric, size, expected):
 )
 def test_graph_metrics_w_constant_values(
     request: pytest.FixtureRequest, metric, array_type
-):
+) -> None:
     if "dask" in array_type.__name__:
         reason = "DaskArray not yet supported"
         request.applymarker(pytest.mark.xfail(reason=reason))
 
+    rng = np.random.default_rng()
+
     # https://github.com/scverse/scanpy/issues/1806
     pbmc = pbmc68k_reduced()
     x_t = pbmc.raw.X.T.copy()
     g = pbmc.obsp["connectivities"].copy()
     equality_check = partial(np.testing.assert_allclose, atol=1e-11)
 
-    const_inds = np.random.choice(x_t.shape[0], 10, replace=False)
+    const_inds = rng.choice(x_t.shape[0], 10, replace=False)
     with warnings.catch_warnings():
         warnings.simplefilter("ignore", sparse.SparseEfficiencyWarning)
         x_t_zero_vals = x_t.copy()
@@ -145,6 +147,43 @@ def test_graph_metrics_w_constant_values(
     equality_check(results_full[non_const_mask], results_const_zeros[non_const_mask])
 
 
+@pytest.mark.parametrize(
+    ("neigh_params", "metric_params"),
+    [
+        pytest.param(
+            dict(key_added="foo"), dict(use_graph="foo_connectivities"), id="use_graph"
+        ),
+        pytest.param(
+            dict(key_added="bar"), dict(neighbors_key="bar"), id="neighbors_key"
+        ),
+    ],
+)
+def test_metrics_graph_params(metric, neigh_params, metric_params) -> None:
+    rng = np.random.default_rng()
+    adata = AnnData(rng.normal(size=(10, 20)))
+    sc.pp.neighbors(adata, **neigh_params)
+    if "use_graph" in metric_params:  # make sure no extra stuff is there
+        adata = AnnData(adata.X, obsp=adata.obsp)
+    metric(adata, **metric_params)
+
+
+@pytest.mark.parametrize(
+    ("params", "err_cls", "pattern"),
+    [
+        pytest.param(
+            dict(use_graph="foo", neighbors_key="bar"), TypeError, r"both", id="both"
+        ),
+        pytest.param(dict(use_graph="foo"), KeyError, r"foo", id="no_graph"),
+        pytest.param(dict(neighbors_key="bar"), KeyError, r"bar", id="no_key"),
+        pytest.param({}, KeyError, r"neighbors.*uns", id="nothing"),
+    ],
+)
+def test_metrics_graph_params_errors(metric, params, err_cls, pattern) -> None:
+    adata = AnnData(shape=(10, 20))
+    with pytest.raises(err_cls, match=pattern):
+        metric(adata, **params)
+
+
 def test_confusion_matrix():
     mtx = sc.metrics.confusion_matrix(["a", "b"], ["c", "d"], normalize=False)
     assert mtx.loc["a", "c"] == 1
@@ -184,10 +223,12 @@ def test_confusion_matrix_randomized() -> None:
     )
 
 
-def test_confusion_matrix_api():
+def test_confusion_matrix_api() -> None:
+    rng = np.random.default_rng()
+
     data = pd.DataFrame({
-        "a": np.random.randint(5, size=100),
-        "b": np.random.randint(5, size=100),
+        "a": rng.integers(5, size=100),
+        "b": rng.integers(5, size=100),
     })
     expected = sc.metrics.confusion_matrix(data["a"], data["b"])